CN114755458B - Intelligent suspension acceleration sensor fault diagnosis method and device - Google Patents
Intelligent suspension acceleration sensor fault diagnosis method and device Download PDFInfo
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- CN114755458B CN114755458B CN202210410234.8A CN202210410234A CN114755458B CN 114755458 B CN114755458 B CN 114755458B CN 202210410234 A CN202210410234 A CN 202210410234A CN 114755458 B CN114755458 B CN 114755458B
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- 230000001133 acceleration Effects 0.000 title claims abstract description 142
- 239000000725 suspension Substances 0.000 title claims abstract description 48
- 238000003745 diagnosis Methods 0.000 title claims abstract description 39
- 238000000034 method Methods 0.000 title claims abstract description 33
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- 239000011159 matrix material Substances 0.000 description 7
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
- G01P21/00—Testing or calibrating of apparatus or devices covered by the preceding groups
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
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Abstract
The invention relates to the technical field of fault diagnosis, in particular to an intelligent suspension acceleration sensor fault diagnosis method and device, comprising the steps of evaluating whether a vertical acceleration sensor of a vehicle has a hardware fault or not through an algorithm, and executing the next step if the vertical acceleration sensor has no hardware fault; dividing the running condition of the vehicle into a stop condition and a running condition by a vehicle speed sensor; acquiring vibration acceleration of the vehicle through a vertical acceleration sensor; calculating the vibration acceleration through a state observer to obtain an optimal estimated value of the vertical vibration speed and a system residual error; judging whether the current signal of the vertical vibration acceleration sensor fails or not based on the optimal estimated value, the system residual error and the running working condition by the suspension ECU controller to obtain a judging result, and solving the problem that the conventional diagnosis method cannot detect the vertical acceleration sensor of the running vehicle in real time.
Description
Technical Field
The invention relates to the technical field of fault diagnosis, in particular to a fault diagnosis method and device for an intelligent suspension acceleration sensor.
Background
The intelligent suspension needs to acquire the vibration state of the vehicle body, and applies a control strategy to generate corresponding output force according to the state information. Therefore, the accuracy and reliability of the state information determine the action effect of the intelligent suspension to a certain extent. To acquire the real-time state of the vehicle, various sensors are indispensable in the vehicle system, of which a vertical acceleration sensor is the most common one for vertical vibration state detection of the vehicle.
However, when the fault diagnosis is performed on the vertical acceleration sensor, the fault diagnosis is performed on the acceleration sensor by using the pre-acquired information of the vehicle when the vehicle is not running, the obtained diagnosis result is the diagnosis result of the vertical acceleration sensor when the information is pre-acquired, the fault condition of the vertical acceleration sensor of the vehicle currently running cannot be obtained, and the accuracy of the diagnosis result of the vertical acceleration sensor is reduced.
Disclosure of Invention
The invention aims to provide a fault diagnosis method and device for an intelligent suspension acceleration sensor, and aims to solve the problem that the conventional diagnosis method cannot detect a vertical acceleration sensor of a running vehicle in real time.
To achieve the above object, in a first aspect, the present invention provides a fault diagnosis method for an intelligent suspension acceleration sensor, including the steps of:
s1, evaluating whether a vertical acceleration sensor of a vehicle has a hardware fault or not through an algorithm, and if the vertical acceleration sensor has no hardware fault, executing a step S2;
s2, dividing the running working condition of the vehicle into a stopping working condition and a running working condition through a vehicle speed sensor;
s3, acquiring vibration acceleration of the vehicle through the vertical acceleration sensor;
s4, calculating the vibration acceleration through a state observer to obtain an optimal estimated value of the vertical vibration speed and a system residual error;
and S5, judging whether the current signal of the vertical vibration acceleration sensor has failed or not by the suspension ECU based on the optimal estimated value, the system residual error and the running working condition, and obtaining a judging result.
The specific way of executing step S2 is that:
s11, when the signal output of the vertical acceleration sensor is a judgment value, delaying for a preset time period;
s12, judging whether the signal output of the vertical acceleration sensor is a judgment value after the delay is finished, if the signal of the vertical acceleration sensor is not the judgment value, the vertical acceleration sensor has no fault, and executing the step S2; if the signal of the vertical acceleration sensor is a judgment value, executing a step S13;
s13, judging that the mode starts to enable the vertical acceleration sensor, and simultaneously, starting to count by a counter, if the count is larger than a preset value, the vertical acceleration sensor has a fault; and if the count is smaller than or equal to the preset value, the signal output of the vertical acceleration sensor is in a condition of being not equal to the judgment value, and the vertical acceleration sensor has no fault, and the step S2 is executed.
The specific way for calculating the vibration acceleration by the state observer to obtain the optimal estimated value of the vertical vibration speed and the system residual error is as follows:
s41, constructing a state equation and an observation equation;
s42, determining an observation error covariance according to the static characteristics of the state observer by using the observation equation;
s43, determining a process noise covariance according to a dynamics model by using the construction state equation;
s44, calculating Kalman gain based on the observed error covariance and the process noise covariance, and obtaining an optimal estimated value of the vertical vibration speed and a system residual error.
The suspension ECU controller judges whether the current signal of the vertical vibration acceleration sensor has failed or not based on the optimal estimated value, the system residual error and the running working condition, and the specific mode for obtaining the judging result is as follows:
s51, judging whether the vertical acceleration sensor has a short circuit or open circuit fault, and if the vertical acceleration sensor does not have a fault, executing a step S52;
s52, judging the current state of the vehicle according to the running condition;
s53, based on the current state, adding an empirical value to the process noise covariance to obtain a threshold range, and delaying for a preset time period when the system residual exceeds the threshold range;
s54, judging whether the system residual error exceeds the threshold range after the delay is finished, if the system residual error is within the threshold range, the vertical acceleration sensor has no fault, and sending a fault prompt to a computer terminal and an instrument panel of the vehicle through a suspension ECU controller, and if the system residual error exceeds the threshold range, executing a step S55;
s55, judging that the mode starts to enable the vertical acceleration sensor, and simultaneously, starting to count the vertical acceleration sensor by the counter, if the count is larger than a preset value, the vertical acceleration sensor has faults, and sending fault reminding to a computer terminal and an instrument panel of the vehicle through the suspension ECU.
Wherein the judgment value is any one of +5V and 0V;
the current state is any one of a running state and a stopped state.
The invention provides an intelligent suspension acceleration sensor fault diagnosis device, which comprises a vertical acceleration sensor, a vehicle speed sensor, a state observer, a suspension ECU controller, an instrument panel and a computer terminal, wherein the vertical acceleration sensor, the state observer, the suspension ECU controller, the instrument panel and the computer terminal are sequentially connected, and the vehicle speed sensor is connected with the suspension ECU controller;
the vehicle speed sensor is used for dividing the running working condition of the vehicle into a stopping working condition and a running working condition;
the vertical acceleration sensor is used for acquiring vibration acceleration of the vehicle;
the state observer is used for calculating the vibration acceleration to obtain an optimal estimated value of the vertical vibration speed and a system residual error;
the suspension ECU controller judges whether the current signal of the vertical vibration acceleration sensor has failed or not based on the optimal estimated value, the system residual error and the running working condition to obtain a judging result;
the instrument panel is used for displaying the judging result in the vehicle;
and the computer terminal is used for remotely displaying the judging result.
According to the intelligent suspension acceleration sensor fault diagnosis method and device, whether the vertical acceleration sensor of the vehicle has hardware faults or not is evaluated through an algorithm, and if the vertical acceleration sensor does not have the hardware faults, the next step is executed; dividing the running working condition of the vehicle into a stopping working condition and a running working condition by a vehicle speed sensor; acquiring vibration acceleration of the vehicle through the vertical acceleration sensor; calculating the vibration acceleration through a state observer to obtain an optimal estimated value of the vertical vibration speed and a system residual error; the suspension ECU controller judges whether the current signal of the vertical vibration acceleration sensor fails or not based on the optimal estimated value, the system residual error and the running working condition to obtain a judging result, and the diagnosis method can realize fault diagnosis on the stopped vehicle and the vertical acceleration sensor of the running vehicle and solve the problem that the conventional diagnosis method cannot detect the vertical acceleration sensor of the running vehicle in real time.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of an intelligent suspension acceleration sensor fault diagnosis method provided by the invention.
Fig. 2 is a flowchart of step S2, in which whether a hardware failure occurs in a vertical acceleration sensor of a vehicle is evaluated by an algorithm, and if no hardware failure occurs in the vertical acceleration sensor.
FIG. 3 is a flow chart of calculating the vibration acceleration by a state observer to obtain an optimal estimate of vertical vibration velocity and a system residual.
Fig. 4 is a flowchart of a judgment result obtained by judging whether the current signal of the vertical vibration acceleration sensor has failed or not by the suspension ECU controller based on the optimal estimated value, the system residual error and the running condition.
Fig. 5 is a schematic structural diagram of fault diagnosis of an intelligent suspension acceleration sensor provided by the invention.
1-vertical acceleration sensor, 2-vehicle speed sensor, 3-state observer, 4-suspension ECU controller, 5-instrument panel, 6-computer terminal.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present invention and should not be construed as limiting the invention.
Referring to fig. 1 to 4, in a first aspect, the present invention provides a fault diagnosis method for an intelligent suspension acceleration sensor, comprising the following steps:
s1, evaluating whether a vertical acceleration sensor 1 of a vehicle has a hardware fault or not through an algorithm, and if the vertical acceleration sensor 1 has no hardware fault, executing a step S2;
the specific method is as follows:
s11 when the signal x of the vertical acceleration sensor 1 is outputted as the judgment value, the preset time period (t 1 Second);
specifically, the judgment value is any one of approximately +5v and approximately 0V, and the diagnosis modes are the same.
S12, judging whether the signal output of the vertical acceleration sensor 1 is a judgment value after the delay is finished, if the signal of the vertical acceleration sensor 1 is not the judgment value, the vertical acceleration sensor 1 has no fault, and executing the step S2; if the signal of the vertical acceleration sensor 1 is a judgment value, executing a step S13;
s13, starting to enable the vertical acceleration sensor 1 in the judging mode, starting to count by a counter, and if the count is larger than a preset value t 2 When the vertical acceleration sensor 1 has faults; if it isThe count is less than or equal to the preset value t 2 When the signal output of the vertical acceleration sensor 1 is not equal to the judgment value, the vertical acceleration sensor 1 has no fault, and the step S2 is executed;
specifically, when the vertical acceleration sensor 1 has no fault, the diagnosis mode is exited, the counter is cleared, and the counter is restarted only when x meets the diagnosis trigger condition, and t 2 Is the calibrated diagnosis time.
S2, dividing the running working condition of the vehicle into a stopping working condition and a running working condition through a vehicle speed sensor 2;
specifically, through the vehicle speed sensor 2, the running condition of the vehicle can be divided into two conditions of stopping and running, when the vehicle speed signal x is output to be 0km/h, the time is delayed for t1 seconds, whether the value of x is 0km/h is judged, if the value of x is 0km/h, the condition judgment mode starts to be enabled, at the moment, the est_cnt starts to be counted, and once the est_cnt is larger than t2, the vehicle is indicated to belong to the stopping condition; when the speed signal x is output to be greater than 0km/h and the rotation speed signal y is greater than 600r/min, delaying for t1 seconds, judging whether the value of x is greater than 0km/h or not and judging whether y is greater than 600r/min, if the speed and rotation speed conditions are met, starting counting by est_cnt, and once est_cnt is greater than t2, indicating that the vehicle belongs to a running condition. Once the enabling condition is not met in the midway, the est_cnt is cleared and exits from the working condition diagnosis mode, and the diagnosis mode is re-entered until the condition is met;
s3, acquiring vibration acceleration of the vehicle through the vertical acceleration sensor 1;
s4, calculating the vibration acceleration through a state observer 3 to obtain an optimal estimated value of the vertical vibration speed and a system residual error;
the specific method is as follows:
s41, constructing a state equation and an observation equation;
specifically, a state equation and an observation equation of the system are built, and a Kalman filter uses a time domain recursion method, so that interference of noise on an observation signal can be eliminated, and a signal which cannot be directly measured by a sensor can be obtained through calculation. Since the acceleration signal and the velocity signal have a simple linear relationship:
v(t+Δt)＝v(t)+a(t)Δt
therefore, the state observer 3 can be designed based on a Kalman filtering algorithm, the state observer 3 is independent of vehicle parameters, an estimation result is not influenced by factors such as vehicle sprung mass, mass center change and the like, a calculation process is simple, and robustness is high. Selecting state variables x 1 ,x 2 The sprung acceleration and sprung velocity of the suspension system are represented, respectively, and the state equation of the system is:
x(k)＝Ax(k-1)+W(k-1)
k represents discrete time, the state variable at k time is x (k), the sampling time of Δt system, a is the state transition matrix of the system, and W represents process noise.
x(k)＝[x 1 (k) x 2 (k)] T
The measurement signal of the system is the sprung mass acceleration of the vehicle, and the observation equation of the system is as follows:
y(k)＝Hx(k)+v(k)
y(k)＝y 1 represents the signal measured by the acceleration sensor, h= [1 0 ]]Representing the observation matrix, v (k) is the measurement noise of the acceleration sensor.
S42, determining an observation error covariance according to the characteristics of the state observer 3 when static by using the observation equation;
s43, determining a process noise covariance according to a dynamics model by using the construction state equation;
assuming that the process noise W and the measurement noise v represent gaussian white noise with a mean value of 0 and uncorrelated with each other, respectively, and their variances are Q and R, respectively;
the gain matrix of the kalman filter is:
wherein: p is the covariance matrix of the error.
S44, calculating Kalman gain based on the observed error covariance and the process noise covariance to obtain an optimal estimated value of the vertical vibration speedAnd system residual->
The predicted value of the system state at the next moment is:
the update equation for the system state variables is:
the error covariance matrix of the system at the next moment is:
P(k+1|k)＝AP(k|k)A T +Q
the update equation of the error covariance matrix is:
P(k+1|k+1)＝(I-K(K+1)H)P(k+1|k)
the system residual matrix equation is:
s5, based on the optimal estimated value and the system residual error through the suspension ECU controller 4And judging whether the current signal of the vertical vibration acceleration sensor fails or not under the driving working condition to obtain a judging result.
The specific method is as follows:
s51, judging whether the vertical acceleration sensor 1 has a fault of short circuit or open circuit, if the vertical acceleration sensor 1 does not have a fault, executing a step S52;
s52, judging the current state of the vehicle according to the running condition;
specifically, the current state is any one of a running state and a stopped state.
S53, based on the current state, adding an empirical value to the process noise covariance to obtain a threshold range, and delaying for a preset time period when the system residual exceeds the threshold range;
specifically, if the car is in a stopped state, the residual error of the systemThe absolute value of (2) should fluctuate within the initial static noise covariance range of the vertical acceleration sensor 1, and a threshold value range z can be set according to the static noise covariance obtained by calibrating the sensor plus an empirical value because the rotation speed of the idle engine may cause small noise vibration error When->When the range is exceeded, the time delay t 1 Second.
S54, judging whether the system residual error exceeds the threshold range after the delay is finished, if the system residual error is within the threshold range, the vertical acceleration sensor 1 has no fault, and sending a fault prompt to a computer terminal 6 and an instrument panel 5 of the vehicle through a suspension ECU controller 4, and if the system residual error exceeds the threshold range, executing a step S55;
and S55, judging that the mode starts to enable the vertical acceleration sensor 1, and simultaneously, starting to count by a counter, if the count is larger than a preset value, the vertical acceleration sensor 1 has a fault, and sending a fault prompt to a computer terminal 6 and an instrument panel 5 of the vehicle through a suspension ECU controller 4.
Specifically, diagnostic mode Start EnableWhen the counter is greater than t2, it is indicated that there is an abnormality in the measurement of the sensor, and the optimal estimated value of the vertical vibration velocity of the vehicle body is obtained from the designed state observer 3The deviation may be large and even have failed, and the observed noise variance needs to be readjusted, at this time, a failure of sensor failure will be reported and sent to the instrument panel 5 and the computer terminal 6 through the suspension ECU controller 4. When the counter counts, once the system residual error is contained in the threshold value, the diagnosis mode is exited, the counter counts again, and the counter begins to count again only when the system residual error meets the diagnosis triggering condition, and t2 is the diagnosis time marked by us.
If the vehicle is in a driving state, the diagnosis principle is similar to that in a stopping state, and it is noted that z error The value of (2) is different from the threshold value of the stop state, and is set to an empirical value according to the characteristics and the allowable range of the sensor.
Referring to fig. 5, in a second aspect, the present invention provides an intelligent suspension acceleration sensor fault diagnosis device, which includes a vertical acceleration sensor 1, a vehicle speed sensor 2, a state observer 3, a suspension ECU controller 4, an instrument panel 5, and a computer terminal 6, wherein the vertical acceleration sensor 1, the state observer 3, the suspension ECU controller 4, the instrument panel 5, and the computer terminal 6 are sequentially connected, and the vehicle speed sensor 2 is connected with the suspension ECU controller 4;
the vehicle speed sensor 2 is used for dividing the running condition of the vehicle into a stop condition and a running condition;
the vertical acceleration sensor 1 is used for acquiring vibration acceleration of the vehicle;
the state observer 3 is configured to calculate the vibration acceleration to obtain an optimal estimated value of a vertical vibration speed and a system residual error;
the suspension ECU controller 4 judges whether the current signal of the vertical vibration acceleration sensor has failed or not based on the optimal estimated value, the system residual error and the running working condition, and obtains a judgment result;
the instrument panel 5 is used for displaying the judging result in the vehicle;
the computer terminal 6 is configured to remotely display the determination result.
Specifically, whether the vertical acceleration sensor 1 of the vehicle has a hardware fault or not is evaluated through an algorithm, and if the vertical acceleration sensor 1 has no hardware fault, the next step is executed; dividing the running condition of the vehicle into a stopping condition and a running condition by a vehicle speed sensor 2; acquiring vibration acceleration of the vehicle through the vertical acceleration sensor 1; calculating the vibration acceleration through a state observer 3 to obtain an optimal estimated value of the vertical vibration speed and a system residual error; the suspension ECU controller 4 judges whether the current signal of the vertical vibration acceleration sensor has failed or not based on the optimal estimated value, the system residual error and the running working condition to obtain a judging result, and the diagnosis method can realize fault diagnosis of the vertical acceleration sensor 1 of the stopped vehicle and the running vehicle.
The foregoing disclosure is only illustrative of a preferred embodiment of a method and apparatus for diagnosing a fault of an intelligent suspension acceleration sensor, but it is not intended to limit the scope of the invention.
Claims (2)
1. The intelligent suspension acceleration sensor fault diagnosis method is characterized by comprising the following steps of:
s1, evaluating whether a vertical acceleration sensor of a vehicle has a hardware fault or not through an algorithm, and if the vertical acceleration sensor has no hardware fault, executing a step S2;
s2, dividing the running working condition of the vehicle into a stopping working condition and a running working condition through a vehicle speed sensor;
s3, acquiring vibration acceleration of the vehicle through the vertical acceleration sensor;
s4, calculating the vibration acceleration through a state observer to obtain an optimal estimated value of the vertical vibration speed and a system residual error;
s5, judging whether the current signal of the vertical vibration acceleration sensor has failed or not by a suspension ECU controller based on the optimal estimated value, the system residual error and the running working condition, and obtaining a judging result;
the algorithm is used for evaluating whether the vertical acceleration sensor of the vehicle has a hardware fault or not, and if the vertical acceleration sensor has no hardware fault, the specific mode of executing the step S2 is as follows:
s11, when the signal output of the vertical acceleration sensor is a judgment value, delaying for a preset time period;
s12, judging whether the signal output of the vertical acceleration sensor is a judgment value after the delay is finished, if the signal of the vertical acceleration sensor is not the judgment value, the vertical acceleration sensor has no fault, and executing the step S2; if the signal of the vertical acceleration sensor is a judgment value, executing a step S13;
s13, judging that the mode starts to enable the vertical acceleration sensor, and simultaneously, starting to count by a counter, if the count is larger than a preset value, the vertical acceleration sensor has a fault; if the count is smaller than or equal to the preset value, the signal output of the vertical acceleration sensor is in a condition of being not equal to the judgment value, and the vertical acceleration sensor has no fault, and the step S2 is executed;
the specific way for calculating the vibration acceleration through the state observer to obtain the optimal estimated value of the vertical vibration speed and the system residual error is as follows:
s41, constructing a state equation and an observation equation;
s42, determining an observation error covariance according to the static characteristics of the state observer by using the observation equation;
s43, determining a process noise covariance according to a dynamics model by using the construction state equation;
s44, calculating Kalman gain based on the observed error covariance and the process noise covariance to obtain an optimal estimated value of the vertical vibration speed and a system residual error;
judging whether the current signal of the vertical vibration acceleration sensor has failed or not by the suspension ECU controller based on the optimal estimated value, the system residual error and the running working condition, wherein the specific mode for obtaining the judging result is as follows:
s51, judging whether the vertical acceleration sensor has a short circuit or open circuit fault, and if the vertical acceleration sensor does not have a fault, executing a step S52;
s52, judging the current state of the vehicle according to the running condition;
s53, based on the current state, adding an empirical value to the process noise covariance to obtain a threshold range, and delaying for a preset time period when the system residual exceeds the threshold range;
s54, judging whether the system residual error exceeds the threshold range after the delay is finished, if the system residual error is within the threshold range, the vertical acceleration sensor has no fault, and sending a fault prompt to a computer terminal and an instrument panel of the vehicle through a suspension ECU controller, and if the system residual error exceeds the threshold range, executing a step S55;
s55, judging that the mode starts to enable the vertical acceleration sensor, and simultaneously, starting to count by a counter, if the count is larger than a preset value, the vertical acceleration sensor has faults, and sending fault reminding to a computer terminal and an instrument panel of the vehicle through a suspension ECU controller;
the judging value is any one of +5V and 0V; the current state is any one of a running state and a stopped state.
2. An intelligent suspension acceleration sensor fault diagnosis device, which applies the intelligent suspension acceleration sensor fault diagnosis method as set forth in claim 1, characterized in that,
the system comprises a vertical acceleration sensor, a vehicle speed sensor, a state observer, a suspension ECU controller, an instrument panel and a computer terminal, wherein the vertical acceleration sensor, the state observer, the suspension ECU controller, the instrument panel and the computer terminal are sequentially connected, and the vehicle speed sensor is connected with the suspension ECU controller;
the vehicle speed sensor is used for dividing the running working condition of the vehicle into a stopping working condition and a running working condition;
the vertical acceleration sensor is used for acquiring vibration acceleration of the vehicle;
the state observer is used for calculating the vibration acceleration to obtain an optimal estimated value of the vertical vibration speed and a system residual error;
the suspension ECU controller judges whether the current signal of the vertical vibration acceleration sensor has failed or not based on the optimal estimated value, the system residual error and the running working condition to obtain a judging result;
the instrument panel is used for displaying the judging result in the vehicle;
and the computer terminal is used for remotely displaying the judging result.
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|---|---|---|---|---|
| CN1918475A (en) * | 2003-12-26 | 2007-02-21 | 博世株式会社 | Failure diagnosis device for vehicle body acceleration sensor and anti-lock brake system |
| KR20080023839A (en) * | 2006-09-12 | 2008-03-17 | 주식회사 만도 | Failure detection method for acceleration sensor in vehicle |
| CN102858607A (en) * | 2011-04-14 | 2013-01-02 | 丰田自动车株式会社 | Device and method for determining abnormality of front/rear acceleration sensor |
| CN108139426A (en) * | 2015-09-30 | 2018-06-08 | 西门子股份公司 | For identifying the method for the failure of acceleration transducer and measuring system |
| CN108445258A (en) * | 2018-04-20 | 2018-08-24 | 北京交通大学 | Magnetic-levitation train list iron suspension acceleration transducer diagnostic method based on integrator |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1918475A (en) * | 2003-12-26 | 2007-02-21 | 博世株式会社 | Failure diagnosis device for vehicle body acceleration sensor and anti-lock brake system |
| KR20080023839A (en) * | 2006-09-12 | 2008-03-17 | 주식회사 만도 | Failure detection method for acceleration sensor in vehicle |
| CN102858607A (en) * | 2011-04-14 | 2013-01-02 | 丰田自动车株式会社 | Device and method for determining abnormality of front/rear acceleration sensor |
| CN108139426A (en) * | 2015-09-30 | 2018-06-08 | 西门子股份公司 | For identifying the method for the failure of acceleration transducer and measuring system |
| CN108445258A (en) * | 2018-04-20 | 2018-08-24 | 北京交通大学 | Magnetic-levitation train list iron suspension acceleration transducer diagnostic method based on integrator |
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